About Ajit Jaokar

#Datascience, #IoT, #MachineLearning, #BigData, Mobile,#Smartcities, #edtech (@feynlabs + @countdowncode) Teaching (@forumoxford + @citysciences). Head of AI for Smart cities lab in Madrid.

Ajit Jaokar Posts (22)

• Data Science for Internet of Things (IoT): Ten Differences From Traditional Data Science - 26 Sep 2016
  
  The connected devices (The Internet of Things) generate more than 2.5 quintillion bytes of data daily. All this data will significantly impact business processes and the Data Science for IoT will take increasingly central role. Here we outline 10 main differences between Data Science for IoT and traditional Data Science.
• Data Science for IoT course: Strategic foundation for decision makers - 09 Sep 2016
  
  The course is based on an open problem solving methodology for IoT analytics which we are developing within the course. The course starts in Sept 2016. To sign up or learn more email info@futuretext.com.
• The Evolution of IoT Edge Analytics: Strategies of Leading Players - 02 Sep 2016
  
  This article explores the significance and evolution of IoT edge analytics. Since the author believes that hardware capabilities will converge for large vendors, IoT analytics will be the key differentiator.
• How to Become a (Type A) Data Scientist - 23 Aug 2016
  
  This post outlines the difference between a Type A and Type B data scientist, and prescribes a learning path on becoming a Type A.
• Data Science for Internet of Things course, Online or London - 21 Jun 2016
  
  Now it is 4th run, the "Data Science for Internet of Things" course is designed to prepare you for the role of a Data Scientist for the Internet of Things(IoT) domain. The course starts in Aug – Sep 2016 , online or in London.
• 3 Telecom Developments Which impact IoT Analytics - 18 Mar 2016
  
  Highlights and developments to watch from Mobile World Congress 2016 which will impact IoT analytics in future.
• Creating a methodology for Data Science for IoT (IoT Analytics) - 13 Jan 2016
  
  While there is no specific methodology to solve Data Science for IoT (IoT Analytics) problems, perhaps it is time to draft one.
• Data Science of IoT: Sensor fusion and Kalman filters, Part 2 - 09 Nov 2015
  
  The second part of this tutorial examines use of Kalman filters to determine context for IoT systems, which helps to combine uncertain measurements in a multi-sensor system to accurately and dynamically understand the physical world.
• Data Science of IoT: Sensor fusion and Kalman filters, Part 1 - 29 Oct 2015
  
  The Kalman filter has numerous applications, including IoT and Sensor fusion, which helps to determine the State of an IoT based computing system based on sensor input.
• The Data Science for Internet of Things – practitioner course - 08 Oct 2015
  
  The Data Science for IoT is the world first course that helps you to become a Data Scientist for the Internet Of Things. Starts Nov 10 in London, UK or online.